[SciPy-Dev] Problem with N-dimensional interpolation using a new griddata function for N>=3
Pauli Virtanen
pav@iki...
Tue Sep 21 07:03:46 CDT 2010
Tue, 21 Sep 2010 13:54:45 +0200, Adam Machnik wrote:
> I have downloaded from SVN the latest `griddata` implementation for
> working in N-D
> with irregular grids (scipy v0.9.0dev6812). It works great for 2D
> problems. However for 3D (and more) I have a problem: the NaN values
> appears always in the same position, and it does not depend on the
> scalar field being interpolated. Here is a small example of simple 3x3x3
> regular grid and a constant scalar field of 1.0 values, that is
> interpolated at the input data points.
Works for me.
grid_z1= [[[ 1. 1. 1.]
[ 1. 1. 1.]
[ 1. 1. 1.]]
[[ 1. 1. 1.]
[ 1. 1. 1.]
[ 1. 1. 1.]]
[[ 1. 1. 1.]
[ 1. 1. 1.]
[ 1. 1. 1.]]]
Do you get the same triangulation?
>>> from scipy.spatial import Delaunay
>>> Delaunay(points).vertices
array([[ 1, 12, 10, 13],
[ 1, 9, 12, 10],
[ 1, 4, 10, 13],
[ 1, 4, 12, 13],
[ 1, 3, 4, 12],
[ 1, 9, 10, 0],
[ 1, 9, 12, 0],
[ 1, 3, 12, 0],
[ 1, 3, 4, 0],
[21, 12, 10, 13],
[21, 22, 12, 13],
[21, 9, 12, 10],
[21, 22, 10, 13],
[21, 19, 22, 10],
[21, 9, 10, 18],
[21, 9, 12, 18],
[21, 19, 10, 18],
[21, 19, 22, 18],
[15, 4, 12, 13],
[15, 16, 12, 13],
[15, 3, 4, 6],
[15, 16, 4, 13],
[15, 7, 16, 4],
[15, 3, 4, 12],
[15, 7, 4, 6],
[15, 7, 16, 6],
[25, 22, 12, 13],
[25, 16, 12, 13],
[25, 21, 22, 24],
[25, 16, 22, 13],
[25, 15, 16, 24],
[25, 21, 12, 24],
[25, 21, 22, 12],
[25, 15, 12, 24],
[25, 15, 16, 12],
[23, 16, 22, 13],
[23, 25, 16, 26],
[23, 14, 16, 13],
[23, 17, 14, 16],
[23, 25, 16, 22],
[23, 17, 16, 26],
[23, 17, 14, 26],
[23, 22, 10, 13],
[23, 14, 10, 13],
[23, 11, 14, 20],
[23, 19, 10, 20],
[23, 19, 22, 10],
[23, 11, 10, 20],
[23, 11, 14, 10],
[ 5, 16, 4, 13],
[ 5, 14, 16, 13],
[ 5, 7, 16, 8],
[ 5, 7, 16, 4],
[ 5, 17, 16, 8],
[ 5, 17, 14, 16],
[ 5, 4, 10, 13],
[ 5, 11, 14, 10],
[ 5, 14, 10, 13],
[ 5, 1, 10, 2],
[ 5, 1, 4, 10],
[ 5, 11, 10, 2]])
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